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An introduction to parallel algorithms

TLDR
This book provides an introduction to the design and analysis of parallel algorithms, with the emphasis on the application of the PRAM model of parallel computation, with all its variants, to algorithm analysis.
Abstract
Written by an authority in the field, this book provides an introduction to the design and analysis of parallel algorithms. The emphasis is on the application of the PRAM (parallel random access machine) model of parallel computation, with all its variants, to algorithm analysis. Special attention is given to the selection of relevant data structures and to algorithm design principles that have proved to be useful. Features *Uses PRAM (parallel random access machine) as the model for parallel computation. *Covers all essential classes of parallel algorithms. *Rich exercise sets. *Written by a highly respected author within the field. 0201548569B04062001

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Posted Content

Low-Depth Parallel Algorithms for the Binary-Forking Model without Atomics.

TL;DR: This paper designs efficient parallel algorithms in the binary-forking model without atomics for three fundamental problems: Strassen's matrix multiplication (MM), comparison-based sorting, and the Fast Fourier Transform (FFT).
Journal ArticleDOI

On the parallel computation of the biconnected and strongly connected co-components of graphs

TL;DR: The results show that, in a parallel process environment, the problems of computing the biconnected components and the strongly connected components can be solved with better time-processor complexity on the complement of a graph rather than on the graph itself.
Journal ArticleDOI

Simpler Sequential and Parallel Biconnectivity Augmentation in Trees

TL;DR: A new sequential algorithm for biconnectivity augmentation in trees is presented by simplifying the algorithm reported in [1], and it is shown that the parallel algorithm is optimal with a processor-time product of O(n) where n is the number of vertices of a tree.
Dissertation

Global optimisation of communication protocols for bulk synchronous parallel computation

TL;DR: It is demonstrated why this is required to implement protocols that both maintain and take into account global state for optimising performance and suggested a regression technique which can be applied to sampled global performance data.
Journal ArticleDOI

Current Trends in Parallel Computing

TL;DR: A survey on current trends in parallel computing has been studied that depicts all the aspects of parallel computing and its usefulness.
References
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Book

Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes

TL;DR: This chapter discusses sorting on a Linear Array with a Systolic and Semisystolic Model of Computation, which automates the very labor-intensive and therefore time-heavy and expensive process of manually sorting arrays.
Book

Computer Architecture and Parallel Processing

Kai Hwang, +1 more
TL;DR: The authors have divided the use of computers into the following four levels of sophistication: data processing, information processing, knowledge processing, and intelligence processing.
Journal ArticleDOI

Data parallel algorithms

TL;DR: The success of data parallel algorithms—even on problems that at first glance seem inherently serial—suggests that this style of programming has much wider applicability than was previously thought.
Proceedings ArticleDOI

Parallelism in random access machines

TL;DR: A model of computation based on random access machines operating in parallel and sharing a common memory is presented and can accept in polynomial time exactly the sets accepted by nondeterministic exponential time bounded Turing machines.
Journal ArticleDOI

The Parallel Evaluation of General Arithmetic Expressions

TL;DR: It is shown that arithmetic expressions with n ≥ 1 variables and constants; operations of addition, multiplication, and division; and any depth of parenthesis nesting can be evaluated in time 4 log 2 + 10(n - 1) using processors which can independently perform arithmetic operations in unit time.